dvsander/mdb-search
Example application querying data in different ways
Demonstrates three distinct MongoDB query patterns on a movie dataset: traditional database search, Lucene-based relevance search with typo correction, and semantic vector search using OpenAI text embeddings (ada-002) and image embeddings (CLIP). The Flask web app stores enriched documents combining operational data with vector embeddings, querying them through MongoDB Atlas Search and Vector Search indexes configured with cosine similarity for both text and image similarity matching.
No commits in the last 6 months.
Stars
16
Forks
5
Language
HTML
License
GPL-3.0
Category
Last pushed
Jul 02, 2024
Commits (30d)
0
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/embeddings/dvsander/mdb-search"
Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.
Higher-rated alternatives
Praful932/Kitabe
Book Recommendation System built for Book Lovers📖. Simply Rate ⭐ some books and get immediate...
passadis/ai-assistant
Books recommendation AI engine
sujee/mongodb-atlas-vector-search
Using MongDB Atlas with embedding models and LLMs to do vector search and RAG applications
Arfazrll/OllamaLLM-RecomendationSystem
An AI book recommendation system built with Streamlit and Ollama. It uses 'nomic-embed-text' for...
ahmedshahriar/TwitterCelebrityMatcher
Match celebrity users with their respective tweets by making use of Semantic Textual Similarity...